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Multiobjective Optimization of multiproduct batch Plants scheduling Under Environmental and Economic Concerns

AICHE JOURNAL 2011年第10期57卷 2766-2782页

作者： Capon-Garcia, Elisabet Bojarski, Aaron D. Espuna, Antonio Puigjaner, Luis Univ Politecn Cataluna Dept Chem Engn CEPIMA ETSEIB E-08028 Barcelona Spain

In hatch process scheduling, production trade-offs arise from the simultaneous consideration of different objectives. Economic goals are expressed in terms of plant profitability and productivity, whereas the environmental objectives are evaluated by means of metrics originated from the use of life cycle assessment methodology. This work illustrates a novel approach for decision making by using multiobjective optimization. In addition, different metrics are proposed to select a possible compromise based on the distance to a nonexistent utopian solution, whose objective function values are all optimal. Thus, this work provides a deeper insight into the influence of the metrics selection for both environmental and economic issues while considering the trade-offs of adopting a particular schedule. The use of this approach is illustrated through its application to a case study related to a multiproduct acrylic fiber production plant, special attention is put to the influence of product changeovers. (C) 2010 American Institute of Chemical Engineers AIChE J, 57: 2766-2782, 2011

关键词： LCA multiobjective optimization multiproduct batch scheduling product changeover

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Multiobjective Evolutionary Optimization of batch Process scheduling Under Environmental and Economic Concerns

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AICHE JOURNAL 2013年第2期59卷 429-444页

作者： Capon-Garcia, Elisabet Bojarski, Aaron D. Espuna, Antonio Puigjaner, Luis ETH Dept Chem & Appl Biosci CH-8093 Zurich Switzerland Univ Politecn Cataluna ETSEIB CEPIMA Dept Chem Engn E-08028 Barcelona Spain

The simultaneous consideration of economic and environmental objectives in batch production scheduling is today a subject of major concern. However, it constitutes a complex problem whose solution necessarily entails production trade-offs. Unfortunately, a rigorous multiobjective optimization approach to solve this kind of problem often implies high computational effort and time, which seriously undermine its applicability to day-to-day operation in industrial practice. Hence, this work presents a hybrid optimization strategy based on rigorous local search and genetic algorithm to efficiently deal with industrial scale batch scheduling problems. Thus, a deeper insight into the combined environmental and economic issues when considering the trade-offs of adopting a particular schedule is provided. The proposed methodology is applied to a case study concerning a multiproduct acrylic fiber production plant, where product changeovers influence the problem results. The proposed strategy stands for a marked improvement in effectively incorporating multiobjective optimization in short-term plant operation. (C) 2012 American Institute of Chemical Engineers AIChE J, 59: 429-444, 2013

关键词： LCA multiobjective optimization evolutionary algorithms multiproduct batch scheduling product changeover sequence dependency

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